Python Automation Testing
Must-haves:
Senior Expertise: 5+ years of experience in QA Automation, with a proven track record of building test automation frameworks from scratch.
GenAI / ML Testing: Hands-on experience testing Large Language Models, RAG architectures, or Machine Learning data pipelines.
Data Quality Mastery: Strong understanding of data preparation, data validation, and SQL/NoSQL querying. Experience curating scalable datasets for model evaluation.
Python Proficiency: Advanced Python programming skills, as the AI ecosystem is heavily Python-centric.
System Design for QA: Ability to architect automated testing strategies for complex, distributed cloud-native microservices.
Nice-to-haves:
Experience working in the eCommerce domain
Knowledge of AgentOps and the lifecycle of autonomous AI agents.
Familiarity with visual IDEs and debugging tools specific to AI development environments.
Strong communication skills to advocate for quality standards across cross-functional teams (Data Engineering, Data Science, and Product).
Essential functions
Must-haves:
Senior Expertise: 5+ years of experience in QA Automation, with a proven track record of building test automation frameworks from scratch.
GenAI / ML Testing: Hands-on experience testing Large Language Models, RAG architectures, or Machine Learning data pipelines.
Data Quality Mastery: Strong understanding of data preparation, data validation, and SQL/NoSQL querying. Experience curating scalable datasets for model evaluation.
Python Proficiency: Advanced Python programming skills, as the AI ecosystem is heavily Python-centric.
System Design for QA: Ability to architect automated testing strategies for complex, distributed cloud-native microservices.
Qualifications
Must-haves:
Senior Expertise: 5+ years of experience in QA Automation, with a proven track record of building test automation frameworks from scratch.
GenAI / ML Testing: Hands-on experience testing Large Language Models, RAG architectures, or Machine Learning data pipelines.
Data Quality Mastery: Strong understanding of data preparation, data validation, and SQL/NoSQL querying. Experience curating scalable datasets for model evaluation.
Python Proficiency: Advanced Python programming skills, as the AI ecosystem is heavily Python-centric.
System Design for QA: Ability to architect automated testing strategies for complex, distributed cloud-native microservices.
Would be a plus
Nice-to-haves:
Experience working in the eCommerce domain
Knowledge of AgentOps and the lifecycle of autonomous AI agents.
Familiarity with visual IDEs and debugging tools specific to AI development environments.
Strong communication skills to advocate for quality standards across cross-functional teams (Data Engineering, Data Science, and Product).
We offer
Opportunity to work on bleeding-edge projects
Work with a highly motivated and dedicated team
Competitive salary
Flexible schedule
Benefits package - medical insurance, sports
Corporate social events
Professional development opportunities
Well-equipped office
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.
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